Image processing method and image processing apparatus

Abstract

The value of the pixel at the same position of each of the training input image as well as a plurality of training feature images is inputted into the discrimination device, which learns in such a way as to reduce the error between the output value obtained from the discrimination device and the value of the pixel at the aforementioned pixel position in the training output image. At the time of enhancement processing, the feature image is produced from the image to be processed, and the values of the pixels of these images at the same position are inputted into the discrimination device, thereby outputting the enhanced image wherein the value outputted from this discrimination device is set as the value of the pixel at the aforementioned pixel position.

1 . An image processing method comprising:
 making a discrimination device learn a specific pattern by using a training image which has the specific pattern and comprises a training input image to be inputted into the discrimination device and a training output image corresponding to the training input image in a learning step; and   creating an enhanced image, on which the specific pattern has been enhanced, from an image to be processed by using the discrimination device in an enhancing step.   
     
     
         2 . The image processing method described in  claim 1 ,
 wherein, in the learning step, a pixel value of a pixel constituting the training input image is inputted into the discrimination device, and a pixel value of a pixel constituting the training output image is used as a learning target value of the discrimination device for the inputted value, whereby the discrimination device learns.   
     
     
         3 . The image processing method described in  claim 1 ,
 wherein a plurality of training input images include a plurality of training feature images created by applying image processing to the training input image, and in the learning step, a pixel value of a pixel of interest located at a corresponding position in each of the plurality of training input images is inputted into the discrimination device, and in the training output image, a pixel value of a pixel corresponding to the pixel of interest is used as a learning target value of the discrimination device for the inputted value.   
     
     
         4 . The image processing method described in  claim 3 ,
 wherein the plurality of training feature images are created in different image processing steps.   
     
     
         5 . The image processing method described in  claim 4 ,
 wherein, in the enhancing step, a plurality of feature images are created by applying different image processing to the image to be processed, and a pixel value of a pixel of interest located at a corresponding position in each of images to be processed including the plurality of feature images is inputted into the discrimination device, and an enhanced image is structured in such a way that an output value outputted based on the inputted value by the discrimination device is used as a pixel value of a pixel corresponding to the pixel of interest.   
     
     
         6 . The image processing method described in  claim 1 ,
 wherein the training output image is an image created by processing the training input image.   
     
     
         7 . The image processing method described in  claim 1 ,
 wherein the training output image is pattern data formed by converting the specific pattern into a function.   
     
     
         8 . The image processing method described in  claim 6 ,
 wherein the pixel value of the training output image is an indiscrete value.   
     
     
         9 . The image processing method described in  claim 6 ,
 wherein the pixel value of the training output image is a discrete value.   
     
     
         10 . The image processing method described in  claim 3 ,
 wherein, in the learning step, the training feature images are grouped according to a characteristic of the image processing applied for the training feature image, and the discrimination device learns according to the group.   
     
     
         11 . The image processing method described in  claim 1 ,
 wherein the training image is a medical image.   
     
     
         12 . The image processing method described in  claim 11 ,
 wherein the training image is a partial image formed by partial extraction from the medical image.   
     
     
         13 . The image processing method described in  claim 11 , wherein the specific pattern indicates an abnormal shadow. 
     
     
         14 . The image processing method described in  claim 1 , further comprising:
 detecting an abnormal shadow candidate by using the enhanced image.   
     
     
         15 . An image processing apparatus comprising:
 a discrimination device for discriminating a specific pattern;   a learning device for making the discrimination device learn the specific pattern by using a training image which has a specific pattern and comprises a training input image to be inputted into the discrimination device and a training output image corresponding to the training input image; and   an enhancing device for creating an enhanced image, on which the specific pattern has been enhanced, from an image to be processed by using the discrimination device.   
     
     
         16 . The image processing apparatus described in  claim 15 ,
 wherein the learning device inputs a pixel value of a pixel constituting the training input image into the discrimination device, and uses a pixel value of a pixel constituting the training output image as a learning target value of the discrimination device for the inputted value, whereby the discrimination device learns.   
     
     
         17 . The image processing apparatus described in  claim 15 ,
 wherein a plurality of training input images include a plurality of training feature images created by applying image processing to the training input image, and the learning device inputs a pixel value of a pixel of interest located at a corresponding position in each of the plurality of training input images into the discrimination device, and in the training output image, uses a pixel value of a pixel corresponding to the pixel of interest as a learning target value of the discrimination device for the inputted value.   
     
     
         18 . The image processing apparatus described in  claim 17 ,
 wherein the plurality of training feature images are created in different image processing steps.   
     
     
         19 . The image processing apparatus described in  claim 18 ,
 wherein the enhancing device creates a plurality of feature images by application of different image processing to the image to be processed, and inputs a pixel value of a pixel of interest located at a corresponding position in each of images to be processed including the plurality of the feature images into the discrimination device, and structures an enhanced image in such a way that an output value outputted based on the inputted value by the discrimination device is used as a pixel value of a pixel corresponding to the pixel of interest.   
     
     
         20 . The image processing apparatus described in  claim 15 ,
 wherein the training output image is an image created by processing the training input image.   
     
     
         21 . The image processing apparatus described in  claim 15 ,
 wherein the training output image is a pattern data formed by converting the specific pattern included in the training input image into a function.   
     
     
         22 . The image processing apparatus described in  claim 20 ,
 wherein the pixel value of the training output image is an indiscrete value.   
     
     
         23 . The image processing apparatus described in  claim 20 ,
 wherein the pixel value of the training output image is an discrete value.   
     
     
         24 . The image processing apparatus described in  claim 17 ,
 wherein the learning device groups the training feature images according to a characteristic of the image processing applied for the training feature image, and the discrimination device learns according to the group.   
     
     
         25 . The image processing apparatus described in  claim 15 ,
 wherein the training image is a medical image.   
     
     
         26 . The image processing apparatus described in  claim 25 ,
 wherein the training image is a partial image formed by partial extraction from the medical image.   
     
     
         27 . The image processing apparatus described in  claim 25 ,
 wherein the specific pattern indicates an abnormal shadow.   
     
     
         28 . The image processing apparatus described in  claim 15 , further comprising:
 an abnormal shadow candidate detecting device for detecting an abnormal shadow candidate by using the enhanced image.